Employment & Productivity

Much has been made of the low level of first-time unemployment claims. They are low, no doubt about it—0.16% of employment, a hair above March’s record low of 0.15% and well below the previous record of 0.20% set in March 2000. (You can say similar things about continuing claims.) But, as we’ve noted in the past, the record comes with an asterisk.

That asterisk is the declining share of the unemployed who are eligible for benefits. When we last visited this terrain, we noted that the insured unemployment rate was close to 70% of the official rate in the early 1970s; it’s less than half that, around 32%, today. Some readers countered that this could be explained by the rising share of the long-term unemployed in the total. True enough; now, those unemployed 27 weeks or longer account for 26% of the total, which would have been worse than a depth-of-recession neighborhood in the 1970s and 1980s.

But the long-termers can’t account for this: initial claims are now around 62% of the flows into unemployment, more than 20 points below the 1990–2007 average of 85%, and had never been below 74% before 2013.

This was basically a solid report, with job growth above recent averages. (Part of that strength was good business practice, and part of it technical, more below.) Wage growth strengthened, but hours were surprisingly weak.

Employers added 200,000 jobs in January, 196,000 of them in the private sector. Both are about 20,000 above the average of the previous six months. Goods production extended its strength, with mining and logging up 6,000 (just above its average over the last year); construction, 36,000 (firmly above average); and manufacturing, 15,000 (slightly below average, with the plus signs concentrated in durables). Private services added 139,000, just above average, with wholesale trade up 10,000 (well above average); retail, 15,000 (quite a contrast with its average of -3,000, with most of the gain coming from clothing stores); transportation and warehousing, 11,000 (just below average); finance, 9,000 (also just below average); professional and business services, 23,000 (more than a third below average, with accounting/bookkeeping in the red for the second consecutive month, and temp firms unusually weak); education and health, 38,000 (just below average, though health care alone was almost a fifth below average); leisure and hospitality, 35,000 (above average); and other services, 6,000 (a third below average). In the red: information, off 6,000, twice its average decline. Government added 4,000, most of it federal, as losses in state gov were offset by gains in local.

As we mentioned in yesterday’s report, seasonal factors anticipated heavy lay-offs in construction and retail work. Surely construction businesses are holding onto their workers in the current environment; those are real jobs, if somewhat enhanced by the factor. The strength in retail, though, was probably driven by weak hiring in December, which caused the factor to over-adjust for anticipated January layoffs.

For the year ending in January, total employment was up 1.5%, and private employment, 1.7%. Both are down 0.2 point from where they were in January 2017 – and both those 2017 numbers were also down 0.2 from January 2016. And the 2016 numbers were down 0.3 (total) and 0.4 (private) from January 2015. Claims that employment growth over the last year have been extraordinary are overdone; the cycle’s peak employment momentum was February 2015’s 2.3%, almost three years ago.

Diffusion indexes were surprisingly weak, with all four intervals down. We wouldn’t make much of this now, but it bears watching.

The average workweek fell 0.2 to 34.3 hours. Declines of 0.2 in the hours series are rare: there have only been seven declines of 0.2 or more (six -0.2s, one -0.3) in since the all-worker series began in March 2006. We’ve seen several instances of 34.3-hour workweeks over the last couple of years, but it is the low end of the range since hours climbed out of the recessionary basement in late 2011. Both manufacturing and services were down.

Average hourly earnings rose 0.3%, taking the three-month moving average up from 0.2% to 0.3%. (We confirmed with the BLS that they have corrected a timing issue affecting wages, so no more fun with that flaw.) The annual gain is now 2.9%, and has risen 0.2pps in each of the last three months. In 2016 the gain for all workers was 2.5%, and in 2017 it was 2.4%. Oddly, you have to go back to June 2009 to see wage growth of 2.9%.

Production and non-supervisory workers’ wages were weaker at 2.4% over the year. We reverse engineered supervisory workers’ wage gains using their share of the workforce, graphed above. You’re see wages for supervisory workers are currently growing at 3.9%. A year ago wages of production workers were growing at 2.3%, while wages for supervisory workers were growing at 2.6%.

Because of the sharp decline in the workweek, aggregate payrolls – hours times earnings times employment – were off 0.1%, the first decline since March 2017.

The benchmark revision announced by the BLS last fall was put in place, once again a non-event. Total employment as of March 2017 was lifted 0.1%, which is below the 0.2% absolute average of the last 10 years. That average has fallen, by the way, which means the monthly estimates have been more accurate in recent years. Over the last five years the revisions were absolute 0.1%. with one too small to count.

This month brought the annual changes to the population controls for the household survey, which makes most month-to-month comparisons non-kosher. The BLS did provide information on several measures adjusted for the changes in the population controls, and those developments were not lapel-grabbing: the participation rate, the employment/population ratio, and the unemployment rate were all unchanged before the changes in the controls, as they were after. And total employment, up 409,000 as published, would have been up just 91,000 were it not for changes to the population controls. The changes increased the size of the noninstitutional population by 488,000, the labor force by 333,000, and employment by 318,000 – not large numbers in the long view, but large enough to muddle comparisons with December.

The unemployment rate has been 4.1% for four consecutive months now. While some analysts are calling for a move towards 3.5%, this stability is starting to look late-cycle-ish.

Weather effects were strictly average for a January.

Because of the changes to the population controls, there is nothing that can be reliably said about the duration of unemployment or the job flows numbers.

The above-consensus rise in employment and strengthening wage growth will bolster the case for further rate rises. It will be interesting to see how dependent on low rates the financial markets and corporate cash flows have become; preliminary signs from stocks suggest there will be some adjustments coming in 2018.

Some people, starting with the Tweeter-in-Chief, have been celebrating a record low in jobless claims. And, as the graph below shows, this is true.

But complicating the picture is the long decline in the share of the unemployed drawing benefits:

Were the share of the unemployed covered by the system the same as it was in 2000, the current level of unemployment claims (as a percentage of employment) would match that low. If it covered the same share of the unemployed as it did in 1979, today’s level would match 1989’s.

The low level of claims is undoubtedly good news, but any notice of that fact should come with an asterisk.

Note: We are looking at long term trends here so this isn’t a big deal, but the Federal Reserve pointed out that Hurricane Harvey is responsible for approximately three-quarters of the decline in the latest industrial production report. Expect the Harvey and Irma effects to be with us for a long time.

Industrial production is the red-headed step-child of coincident economic statistics. The entire market stops, and then quickly restarts, when the BLS releases the employment report. The Census’s retail sales number receives less fanfare, but it does have a certain amount of headline grabbing power despite its unruly nature. In contrast, the Federal Reserve’s industrial production release receives no attention. This is unfortunate, because it contains a great deal of salient information. And there is no disputing its economic importance: according to BEA industry output data, manufacturing is one of the largest contributors to total industry output.

Before looking at the latest report, let’s consider some context:

The above chart shows all the primary coincident indicators shifted to base 100. All – except industrial production – have risen above their respective pre-recession highs. It peaked at the end of 2015, dipped for a few years, and only recently increased to higher levels.

Next, consider capacity utilization:

This statistic has hit consistently lower peaks for the last three expansions. This has two important ramifications. First, it weakens investment demand. Why add to your physical plant when you’re employing a lower percentage of it? Second, this may be a fundamental reason for weak price pressures. Why raise prices when instead all you have to do is bring more of your dormant capacity online?

There are two categorization systems used by the Federal Reserve to break down industrial production: major industry groups and major market groups. We will take those in turn.

Major Industry Groups

We’ll break this data down into 4 sub-components, starting with durable and nondurable manufacturing.

Durable manufacturing (in red) first peaked in mid-20124 and again in 2017. But it still hasn’t advanced much beyond its pre-recession level. It’s doubtful it will do so; auto sales are declining and the auto dealer sales/inventory ratio is near a multi-decade high. Non-durable goods dropped about 10% during the recession and only recently started to rise from the pre-recession lows.

Here are the charts of the final two industry groups:

Utilities (top chart) have moved sideways for the duration of this expansion. We suspect increased energy efficiency is having an impact, a good thing. That leaves mining (bottom chart) to provide the sold growth engine. It declined for 30 years (1980-2010) before growing strongly because of the fracking revolution. That has proved to be an unstable thing, but if it weren’t for fracking, there would be no major move in industrial production along industry lines.

Market Groups

Let’s first look at industrial production for consumer goods:

Durable production (in red) has risen to slightly above pre-recession levels, but has yet to move meaningfully beyond that level. Nondurable production (in blue) remains below its prerecession level – so much so that it’s highly doubtful it will advance beyond its previous high.

Next, here is business equipment:

Business equipment (in green) is stuck near its pre-recession level. Construction production (in red) was understandably high during the housing bubble. It dropped sharply during the recession and has been rising consistently since. General business supplies (in blue) is still far below pre-recession levels.

Defense and space production has recently declined:

Next is durables and nondurables materials production:

Durables production (in blue) is slightly above it pre-recession level while nondurable goods are sharply lower. There has been no meaningful growth in either measure dor at least several years.

Energy is the last industry classification:

And it is the only one that has meaningfully grown during this expansion.

Regardless of how you slice the data, The United States’ physical production hasn’t grown meaningfully during this expansion. The best performing sector in the consumer areas is durables, and they’re still near pre-recession levels. Overall business supplies levels are also lackluster. If it weren’t for oil, we’d be seeing no growth in industrial production.

Productivity is one of our obsessions, and it should be a national obsession as well.* Clearly it isn’t. The industry statistics presented here show that for a lot of industries, the last couple of years have been a real bust.

The stats, provided by the Bureau of Labor Statistics, cover scores of industries, with the manufacturing sub-sectors particularly finely broken down. Here we’ve provided what is fashionably described in some circles as a “curated” list of industries, since the whole set is beyond our scope.

First the long sweep, from 1987 (when this series begins) through 2016, graphed below. (The 2016 data isn’t available for all industries; those for which 2015 is the terminal year are marked with an asterisk in all three graphs.) The standouts are, not surprisingly, in high-tech: computers, semiconductors, and software, all with annual gains in the double digits. Some old-line industries, like motor vehicles, aircraft, and wholesale and retail trade, turned in solid performances.

Eating and drinking establishments and, perhaps surprisingly, pharmaceuticals did quite poorly, with pharma slightly in the red—an amazing, if invisible on the graph, feat for such a technology-rich enterprise. And perhaps even more surprisingly, the postal service did better than private couriers and messengers, where productivity declined over the almost three-decade interval.

But as the graph below shows, most of the stellar performances were logged during the productivity acceleration of the late 1990s and early 2000s. Of the 22 industries shown, 20 saw a decline between that period and the last twelve years—a decline of over 4 percentage points on average. Only mining and aircraft showed a pickup. Computers and semiconductors fell by around 20 percentage points. Pharmaceuticals went from positive to negative.

And the last couple of years have been fairly terrible. Half the industries showed a decline in productivity. Only mining—fracking, one assumes—had a strong performance. Computers remained in the black, but semiconductors fell below zero. Motor vehicles and medical equipment were firmly negative.

The productivity slowdown that we’ve been following at a high level is a pervasive problem at the industry level.

* For those of you not so obsessed, productivity determines our standard of living. An increase in productivity means greater output from the same input, which makes labor more valuable, which in turn lifts wages. Too many corporations are currently using their profits, and money borrowed on the cheap, to buy back their own stock and pay dividends to their investors instead of investing in productivity enhancing research & development, and physical capital. That’s one of the big factors in sluggish wage growth.